Model Context Protocol
Extends large language model capabilities through tool invocation directly within the model's text output.
About
This repository provides a Flask-based implementation of the Model Context Protocol (MCP), enabling LLMs to leverage external tools through natural language interactions. Unlike traditional function calling, MCP places tool definitions directly within the context window, allowing the model to invoke tools using natural language responses, which are then parsed and executed. The server includes sample tools like weather and calculator, demonstrates conversation flow, and utilizes regex-based parsing for flexible tool invocation.
Key Features
- Uses regex-based parsing for flexible text parsing of tool invocations.
- Includes sample weather and calculator tools with parameter validation.
- Maintains context across multiple interactions.
- Flask API provides REST endpoints for chat integration.
- Complete MCP implementation with parsing, execution, and response handling.
Use Cases
- Enhancing chatbot functionality with real-time information (e.g., weather data).
- Building conversational agents capable of interacting with external APIs.
- Enabling LLMs to perform calculations or data analysis tasks.
Sponsored